OBJECTIVE: To investigate the predictive value of inflammatory indicator and serum cystatin C (Cys C) for the prognosis of patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A prospective observational study was conducted. Patients with SA-AKI admitted to the intensive care unit (ICU) of the General Hospital of Ningxia Medical University from January 2022 to December 2023 were selected as the study subjects. General patient data, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II (APACHE II), inflammatory indicator, and serum Cys C levels were collected. The 28-day survival status of the patients was observed. A multivariate Logistic regression model was used to analyze the risk factors affecting the poor prognosis of SA-AKI patients. Receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive efficacy of each risk factor for the prognosis of SA-AKI patients. RESULTS: A total of 111 SA-AKI patients were included, with 65 patients (58.6%) in the survival group and 46 patients (41.4%) in the death group. The SOFA score, APACHE II score, interleukin-6 (IL-6), procalcitonin (PCT), hypersensitive C-reactive protein (hs-CRP), and serum Cys C levels in the death group were significantly higher than those in the survival group [SOFA score: 15.00 (14.00, 17.25) vs. 14.00 (11.00, 16.00), APACHE II score: 26.00 (23.75, 28.00) vs. 23.00 (18.50, 28.00), IL-6 (ng/L): 3 731.00±1 573.61 vs. 2 087.93±1 702.88, PCT (μg/L): 78.19±30.35 vs. 43.56±35.37, hs-CRP (mg/L): 266.50 (183.75, 326.75) vs. 210.00 (188.00, 273.00), serum Cys C (mg/L): 2.01±0.61 vs. 1.62±0.50, all P < 0.05]. Multivariate Logistic regression analysis showed that SOFA score [odds ratio (OR) = 1.273, 95% confidence interval (95%CI) was 1.012-1.600, P = 0.039], IL-6 (OR = 1.000, 95%CI was 1.000-1.001, P = 0.043), PCT (OR = 1.018, 95%CI was 1.002-1.035, P = 0.030), and Cys C (OR = 4.139, 95%CI was 1.727-9.919, P = 0.001) were independent risk factors affecting the 28-day prognosis of SA-AKI patients. ROC curve analysis showed that the area under the curve (AUC) of SOFA score, IL-6, PCT, and Cys C in predicting the 28-day prognosis of SA-AKI patients were 0.682 (95%CI was 0.582-0.782, P = 0.001), 0.753 (95%CI was 0.662-0.843, P < 0.001), 0.765 (95%CI was 0.677-0.854, P < 0.001), and 0.690 (95%CI was 0.583-0.798, P = 0.001), respectively. The combined predictive value of these four indicators for the prognosis of SA-AKI patients were superior to that of any single indicator, with an AUC of 0.847 (95%CI was 0.778-0.916, P < 0.001), a sensitivity of 95.7%, and a specificity of 56.9%. CONCLUSION The combination of SOFA score, IL-6, PCT, and Cys C provides a reliable predictive value for the prognosis of SA-AKI patients.
Humans ; Acute Kidney Injury/mortality* ; APACHE ; C-Reactive Protein ; Cystatin C/blood* ; Interleukin-6/blood* ; Logistic Models ; Predictive Value of Tests ; Procalcitonin/blood* ; Prognosis ; Prospective Studies ; Risk Factors ; ROC Curve ; Sepsis/mortality*

OBJECTIVE: To assess the relationship between blood pressure reactivity index (BPRI) and in-hospital mortality risk in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A retrospective cohort study was conducted to collect data from patients admitted to the intensive care unit (ICU) and clinically diagnosed with SA-AKI between 2008 and 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. The collected data included demographic characteristics, comorbidities, vital signs, laboratory parameters, sequential organ failure assessment (SOFA) and simplified acute physiology scoreII(SAPSII) within 48 hours of SA-AKI diagnosis, stages of AKI, treatment regimens, mean BPRI during the first and second 24 hours (BPRI_0_24, BPRI_24_48), and outcome measures including primary outcome (in-hospital mortality) and secondary outcomes (ICU length of stay and total hospital length of stay). Variables with statistical significance in univariate analysis were included in LASSO regression analysis for variable selection, and the selected variables were subsequently incorporated into multivariate Logistic regression analysis to identify independent predictors associated with in-hospital mortality in SA-AKI patients. Restricted cubic spline (RCS) analysis was employed to examine whether there was a linear relationship between BPRI within 48 hours and in-hospital mortality in SA-AKI patients. Basic prediction models were constructed based on the independent predictors identified through multivariate Logistic regression analysis, and receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive performance of each basic prediction model before and after incorporating BPRI. RESULTS: A total of 3 517 SA-AKI patients admitted to the ICU were included, of whom 826 died during hospitalization and 2 691 survived. The BPRI values within 48 hours of SA-AKI diagnosis were significantly lower in the death group compared with the survival group [BPRI_0_24: 4.53 (1.81, 8.11) vs. 17.39 (5.16, 52.43); BPRI_24_48: 4.76 (2.42, 12.44) vs. 32.23 (8.85, 85.52), all P < 0.05]. LASSO regression analysis identified 20 variables with non-zero coefficients that were included in the multivariate Logistic regression analysis. The results showed that respiratory rate, temperature, pulse oxygen saturation (SpO₂), white blood cell count (WBC), hematocrit (HCT), activated partial thromboplastin time (APTT), lactate, oxygenation index, SOFA score, fluid balance (FB), BPRI_0_24, and BPRI_24_48 were all independent predictors for in-hospital mortality in SA-AKI patients (all P < 0.05). RCS analysis revealed that both BPRI showed "L"-shaped non-linear relationships with the risk of in-hospital mortality in SA-AKI patients. When BPRI_0_24 ≤ 14.47 or BPRI_24_48 ≤ 24.21, the risk of in-hospital mortality in SA-AKI increased as BPRI values decreased. Three basic prediction models were constructed based on the identified independent predictors: Model 1 (physiological indicator model) included respiratory rate, temperature, SpO₂, and oxygenation index; Model 2 (laboratory indicator model) included WBC, HCT, APTT, and lactate; Model 3 (scoring indicator model) included SOFA score and FB. ROC curve analysis showed that the predictive performance of the basic models ranked from high to low as follows: Model 3, Model 2, and Model 1, with area under the curve (AUC) values of 0.755, 0.661, and 0.655, respectively. The incorporation of BPRI indicators resulted in significant improvement in the discriminative ability of each model (all P < 0.05), with AUC values increasing to 0.832 for Model 3+BPRI, 0.805 for Model 2+BPRI, and 0.808 for Model 1+BPRI. CONCLUSIONS BPRI is an independent predictor factor for in-hospital mortality in SA-AKI patients. Incorporating BPRI into the prediction model for in-hospital mortality risk in SA-AKI can significantly improve its predictive capability.
Humans ; Acute Kidney Injury/mortality* ; Sepsis/complications* ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Blood Pressure ; Intensive Care Units ; Male ; Female ; Length of Stay ; Middle Aged ; Aged ; Adult ; Logistic Models

OBJECTIVE: To identify and validate novel biomarkers for the early diagnosis of sepsis-associated acute kidney injury (SA-AKI) and precise continuous renal replacement therapy (CRRT) using proteomics. METHODS: A prospective multicenter cohort study was conducted. Patients with sepsis admitted to five hospitals in Taizhou City of Zhejiang Province from April 2019 to December 2021 were continuously enrolled, based on the occurrence of acute kidney injury (AKI). Sepsis patients were divided into SA-AKI group and non-SA-AKI group, and healthy individuals who underwent physical examinations during the same period were used as control (NC group). Peripheral blood samples from participants were collected for protein mass spectrometry analysis. Differentially expressed proteins were identified, and functional enrichment analysis was conducted on these proteins. The levels of target proteins were detected by enzyme linked immunosorbent assay (ELISA), and the predictive value of target protein for SA-AKI were evaluated by receiver operator characteristic curve (ROC curve). Additionally, sepsis patients and healthy individuals were selected from one hospital to externally verify the expression level of the target protein and its predictive value for SA-AKI, as well as the accuracy of CRRT treatment. RESULTS: A total of 37 patients with sepsis (including 19 with AKI and 18 without AKI) and 31 healthy individuals were enrolled for proteomic analysis. Seven proteins were identified with significantly differential expression between the SA-AKI group and non-SA-AKI group: namely cystatin C (CST3), β ₂-microglobulin (β ₂M), insulin-like growth factor-binding protein 4 (IGFBP4), complement factor I (CFI), complement factor D (CFD), CD59, and glycoprotein prostaglandin D2 synthase (PTGDS). Functional enrichment analysis revealed that these proteins were involved in immune response, complement activation, coagulation cascade, and neutrophil degranulation. ELISA results demonstrated specific expression of each target protein in the SA-AKI group. Additionally, 65 patients with sepsis (38 with AKI and 27 without AKI) and 20 healthy individuals were selected for external validation of the 7 target proteins. ELISA results showed that there were statistically significant differences in the expression levels of CST3, β ₂M, IGFBP4, CFD, and CD59 between the SA-AKI group and non-SA-AKI group. ROC curve analysis indicated that the area under the curve (AUC) values of CST3, β ₂M, IGFBP4, CFD, and CD59 for predicting SA-AKI were 0.788, 0.723, 0.723, 0.795, and 0.836, respectively, all exceeding 0.7. Further analysis of patients who underwent CRRT or not revealed that IGFBP4 had a good predictive value, with an AUC of 0.84. CONCLUSIONS Based on proteomic analysis, CST3, β ₂M, IGFBP4, CFD, and CD59 may serve as potential biomarkers for the diagnosis of SA-AKI, among which IGFBP4 might be a potential biomarker for predicting the need for CRRT in SA-AKI patients. However, further clinical validation is required.
Humans ; Sepsis/complications* ; Acute Kidney Injury/blood* ; Proteomics ; Prospective Studies ; Biomarkers/blood* ; Male ; Female ; beta 2-Microglobulin/blood* ; Middle Aged ; Cystatin C/blood* ; Aged

INTRODUCTION: Acute severe ulcerative colitis (ASUC) is a significant cause of disease morbidity. One-third of patients with ASUC are steroid refractory. Rescue therapy may not successfully induce remission, necessitating colectomy. We aimed to identify predictors of rescue therapy and colectomy in ASUC assessed within 24 h of admission for early risk stratification. METHODS: We conducted a retrospective cohort study of 58 admissions for ASUC among 47 patients from August 2002 to January 2022. Serum biomarkers assessed were measured on admission. Primary outcomes were the need for rescue therapy during the same admission and colectomy within 1 year of admission. RESULTS: Rescue therapy (all with infliximab) was given in 20 (34.5%) of the admissions. Colectomy was done within 1 year for nine (15.5%) of the admissions. An elevated C-reactive protein (CRP) of >30 mg/L (relative risk [RR] 1.63), a CRP-albumin ratio of >0.85 (RR 1.63), and a composite factor of both CRP > 30 mg/L and age ≥60 years (RR 2.37) were significantly associated with the need for rescue therapy. Hypoalbuminaemia ≤ 25 g/L (RR 4.35) and the use of biologics at presentation (RR 1.54) were significantly associated with colectomy within 1 year of admission, while a CRP of ≥ 80 mg/L was a significant protective factor (RR 0.70). CONCLUSION Patients with ASUC who have elevated CRP or CRP-albumin ratio on admission should be considered at risk for steroid-refractory disease. Those with hypoalbuminaemia on admission and using biologics at presentation are more likely to require colectomy in the first year after admission for ASUC.
Humans ; Colitis, Ulcerative/therapy* ; Colectomy ; Retrospective Studies ; Male ; Female ; Middle Aged ; Adult ; C-Reactive Protein/metabolism* ; Infliximab/therapeutic use* ; Biomarkers/blood* ; Acute Disease ; Aged ; Severity of Illness Index ; Treatment Outcome

INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers age, sex and cardiac troponin I (TnI) results to risk-stratify patients for type 1 myocardial infarction. METHOD: Patients aged ≥25 years who presented to the emergency department (ED) of Singapore General Hospital with symptoms suggestive of acute coronary syndrome with no diagnostic 12-lead electrocardiogram (ECG) changes were included. Participants had serial ECGs and high-sensitivity troponin assays performed at 0, 2 and 7 hours. The primary outcome was the adjudicated diagnosis of type 1 myocardial infarction at 30 days. We compared the performance of MI3 in predicting the primary outcome with the European Society of Cardiology (ESC) 0/2-hour algorithm as well as the 99th percentile upper reference limit (URL) for TnI. RESULTS: There were 1351 patients included (66.7% male, mean age 56 years), 902 (66.8%) of whom had only 0-hour troponin results and 449 (33.2%) with serial (both 0 and 2-hour) troponin results available. MI3 ruled out type 1 myocardial infarction with a higher sensitivity (98.9, 95% confidence interval [CI] 93.4-99.9%) and similar negative predictive value (NPV) 99.8% (95% CI 98.6-100%) as compared to the ESC strategy. The 99th percentile cut-off strategy had the lowest sensitivity, specificity, positive predictive value and NPV. CONCLUSION The MI3 algorithm was accurate in risk stratifying ED patients for myocardial infarction. The 99th percentile URL cut-off was the least accurate in ruling in and out myocardial infarction compared to the other strategies.
Humans ; Male ; Female ; Emergency Service, Hospital ; Middle Aged ; Electrocardiography ; Machine Learning ; Singapore ; Chest Pain/blood* ; Troponin I/blood* ; Myocardial Infarction/blood* ; Risk Assessment/methods* ; Aged ; Algorithms ; Acute Coronary Syndrome/blood* ; Adult ; Sensitivity and Specificity

OBJECTIVE: To investigate platelet count trajectories after induction therapy with venetoclax combined with azacitidine (VA regimen) in newly diagnosed AML patients and further analyze its clinical significance. METHODS: Clinical date of 50 newly diagnosed AML patients who received VA treatment from March 2020 to July 2023 in Department of Hematology of the First Hospital of Lanzhou University were retrospectively collected. The platelet trajectories after induction chemotherapy were constructed by using group-based trajectory modeling. To study the association between diverse trajectories of platelet counts and compound complete remission (cCR) rate, overall response rate (ORR), minimal residual disease (MRD) negative rate and overall survival (OS) rate. The Cox proportional hazard model was used to evaluate the relationship between platelet trajectory and OS. The logistic regression was used to analyze the influence of individual characteristics on platelet trajectory. RESULTS: Two platelet trajectories were identified based on the model, including platelet slowly increased group (n=31, 62.0%) and platelet rapidly increased group (n=19, 38.0%). There were statistically significant differences in cCR rate, ORR and OS rate between platelet slowly increased group and platelet rapidly increased group (all P < 0.05). The Cox regression analysis showed that platelet rapidly increased group was associated with a decreased risk of mortality compared with platelet slowly increased group (HR=0.153, 95%CI : 0.045-0.527, P =0.003). Logistic regression analysis showed that IDH1/2 mutation (OR =3.908, 95%CI : 1.023-14.923, P =0.046) and platelet transfusion (OR =0.771, 95%CI : 0.620-0.959, P =0.020) were independent influencing factors of platelet trajectory. CONCLUSION The dynamic trajectory of platelet counts in newly diagnosed AML patients who received VA treatment can serve as a significant indicator to observe the efficacy and prognosis. The platelet rapidly increased is an independent protective factor for good prognosis. TheIDH1 /2 mutation and platelet transfusion are independent influencing factors of platelet trajectory.
Humans ; Leukemia, Myeloid, Acute/blood* ; Sulfonamides/administration & dosage* ; Azacitidine/therapeutic use* ; Platelet Count ; Retrospective Studies ; Bridged Bicyclo Compounds, Heterocyclic/administration & dosage* ; Male ; Female ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Induction Chemotherapy ; Survival Rate

OBJECTIVES: Hypertriglyceridemic acute pancreatitis (HTG-AP) has a rapid onset and is associated with a high risk of progression and recurrence. Early identification of patients at risk of severe disease can help reduce the likelihood of multiple organ failure and mortality. This study aims to investigate the changes in inflammatory composite markers and D-dimer (D-D) levels in young and middle-aged/elderly patients with HTG-AP and to evaluate their predictive value for disease progression. METHODS: A total of 230 patients with HTG-AP admitted to Chongqing University Jiangjin Hospital (Jiangjin Central Hospital) between 2017 and 2023 were retrospectively enrolled. Patients were first divided into a young group (≤45 years) and a middle-aged/elderly group (>45 years), and then stratified into mild and severe groups based on disease severity. Inflammatory composite markers, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), C-reactive protein-to-lymphocyte ratio (CLR), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), as well as D-D levels, were compared among groups. Least absolute shrinkage and selection operator (LASSO) regression and Logistic regression were used to identify independent risk factors for disease progression in each age group. Receiver operating characteristic (ROC) curves and the DeLong test were used to assess and compare the predictive performance (area under the curve, AUC) of risk factors. Internal validation was performed using the bootstrap method (n=1 000). RESULTS: No significant differences in NLR, PLR, MLR, SIRI, SII, CLR, or D-D levels were observed between the young (n=127) and middle-aged/elderly (n=103) groups (all P>0.05). Among young patients, the severe group (n=59) had significantly higher NLR, SIRI, SII, CLR, and D-D levels compared to the mild group (n=68) (all P<0.05). Among middle-aged/elderly patients, CLR and D-D levels were significantly higher in the severe group (n=49) than in the mild group (n=54) (P<0.05). LASSO and Logistic regression analyses identified elevated D-D as an independent risk factor for disease progression in young patients (P=0.007, OR=1.458, 95% CI 1.107 to 1.920), while both D-D (P=0.001, OR=2.267, 95% CI 1.413 to 3.637) and CLR (P=0.003, OR=1.007, 95% CI 1.003 to 1.012) were independent risk factors in middle-aged/elderly patients. ROC analysis showed that D-D predicted disease progression in young and middle-aged/elderly patients with AUCs of 0.653 and 0.741, sensitivities of 67.8% and 57.1%, and specificities of 72.1% and 88.9%, respectively. CLR predicted progression in middle-aged/elderly patients with an AUC of 0.687, sensitivity of 63.3%, and specificity of 70.4%. DeLong test showed no significant difference in AUC between D-D and CLR for middle-aged/elderly patients (Z=0.993, P=0.321). Internal validation via bootstrap analysis yielded a D-D AUC of 0.732, with sensitivity and specificity of 68.1% and 91.0%, respectively. CONCLUSIONS Differences in inflammatory response and coagulation function exist across age groups and disease severities in HTG-AP patients. Elevated D-D is an independent predictor of disease progression in both young and middle-aged/elderly patients, while CLR also predicts progression in the latter group. D-D, in particular, demonstrates strong predictive value for severe disease in middle-aged/elderly patients with HTG-AP.
Humans ; Fibrin Fibrinogen Degradation Products/metabolism* ; Disease Progression ; Middle Aged ; Pancreatitis/etiology* ; Male ; Female ; Retrospective Studies ; Adult ; Biomarkers/blood* ; Hypertriglyceridemia/blood* ; Acute Disease ; Predictive Value of Tests ; Aged ; Inflammation ; C-Reactive Protein/analysis* ; Neutrophils ; Age Factors

Coronavirus disease 2019 (COVID-19) is a multi-system disease that can lead to various severe complications. Acute limb ischemia (ALI) has been increasingly recognized as a COVID-19-associated complication that often predicts a poor prognosis. However, the pathophysiology and molecular mechanisms underlying COVID-19-associated ALI remain poorly understood. Hypercoagulability and thrombosis are considered important mechanisms, but we also emphasize the roles of vasospasm, hypoxia, and acidosis in the pathogenesis of the disease. The angiotensin-converting enzyme 2 (ACE2) pathway, inflammation, and platelet activation may be important molecular mechanisms underlying these pathological changes induced by COVID-19. Furthermore, we discuss the hypotheses of risk factors for COVID-19-associated ALI from genetic, age, and gender perspectives based on our analysis of molecular mechanisms. Additionally, we summarize therapeutic approaches such as use of the interleukin-6 (IL-6) blocker tocilizumab, calcium channel blockers, and angiotensin-converting enzyme inhibitors, providing insights for the future treatment of coronavirus-associated limb ischemic diseases.
Humans ; COVID-19/physiopathology* ; Ischemia/etiology* ; SARS-CoV-2 ; Extremities/blood supply* ; Risk Factors ; Interleukin-6/antagonists & inhibitors* ; Acute Disease ; Angiotensin-Converting Enzyme 2

OBJECTIVES: To explore the correlation of serum tryptophan level with 90-day mortality risk in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). METHODS: This retrospective study was conducted among 108 patients with HBV-ACLF, whose survival outcomes within 90 days after diagnosis were recorded. The correlation of baseline serum tryptophan levels measured by high-performance liquid chromatography with 90-day mortality of the patients was analyzed, and the predictive value of serum tryptophan for 90-day mortality was explored. RESULTS: Within 90 days after diagnosis, 53 (29.4%) of the patients died and 127 (70.6%) survived. The deceased patients had significantly lower baseline serum tryptophan levels than the survivors (7.31±3.73 pg/mL vs 13.32±7.15 pg/mL, P<0.001). Multivariate analysis suggested that serum tryptophan level was an independent factor correlated with mortality of HBV-ACLF after adjustment for confounding variables. The patients with serum tryptophan levels below the median level (10.14 pg/mL) at admission had significantly higher 90-day mortality risks than those with higher tryptophan levels (43.3% vs 15.6%, HR: 3.157, 95% CI: 1.713-5.817), and the complication by kidney dysfunction further increased the risk to 73.3% as compared with patients with higher serum tryptophan levels with normal kidney function (15.0%; HR: 7.558, 95% CI: 3.369-16.960). Serum tryptophan levels had an area under the receiver operating characteristic curve of 0.771 (95% CI: 0.699-0.844) for predicting 90-day mortality. CONCLUSIONS Serum tryptophan level is closely correlated with the survival outcomes of patients with HBV-ACLF, and a decreased tryptophan level indicates a high 90-day mortality risk, which can be further increased by the complication by kidney dysfunction.
Humans ; Tryptophan/blood* ; Retrospective Studies ; Acute-On-Chronic Liver Failure/virology* ; Male ; Female ; Middle Aged ; Adult ; Prognosis ; Hepatitis B/complications* ; Hepatitis B virus

OBJECTIVES: To evaluate the correlation of mean arterial oxygen tension (PaO₂) during the first 24 h following intensive care unit (ICU) admission with mortality in critically ill patients with acute kidney injury (AKI) and determine the optimal PaO₂ threshold for devising oxygen therapy strategies for these patients. METHODS: We collected the clinical data of ICU patients with AKI from the MIMIC-IV database. Based on the optimal first 24-h PaO₂ threshold determined by receiver operating characteristic (ROC) curve analysis and the Youden index maximization principle, we classified the patients into hyperoxia group (with PaO₂ ≥137.029 mmHg) and hypoxemia group (PaO₂<137.029 mm Hg). Multivariable logistic regression and propensity score matching were used to evaluate the correlation of first 24-h PaO₂ levels with in-hospital mortality of the patients. RESULTS: Among the 18 335 patients, 46.7% were in the hyperoxia group, who had an overall mortality rate of 16.9%. The optimal PaO₂ threshold (137.029 mm Hg) had a sensitivity of 78.3%, a specificity of 63.7%, and an AUC of 0.76 (95% CI: 0.74=0.78). Hyperoxia within the first 24 h after ICU admission was associated with a significantly lower in-hospital mortality (OR=0.78) and 90-day mortality (OR=0.77), particularly in stage 1 AKI patients. A non-linear relationship was identified between PaO₂ and mortality of the patients (P<0.001). Kaplan-Meier survival curves indicated a significantly increased 90-day survival rate in the patients in hyperoxia group (P<0.001), who also had shorter durations of mechanical ventilation, less vasopressor use, and shorter lengths of hospital/ICU stay. CONCLUSIONS Maintenance of a PaO₂ level ≥137.029 mmHg within 24 h after ICU admission may improve clinical outcomes of critically ill AKI patients, which underscores the importance of targeted oxygen delivery in ICU care.
Humans ; Acute Kidney Injury/blood* ; Male ; Female ; Middle Aged ; Intensive Care Units ; Aged ; Oxygen/blood* ; Hospital Mortality ; Partial Pressure ; Adult ; Databases, Factual